






import os
from shutil import copyfile
from typing import List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


UpperCamelCase								=		logging.get_logger(__name__)

UpperCamelCase								=		{'''vocab_file''': '''sentencepiece.model'''}

UpperCamelCase								=		{
    '''vocab_file''': {
        '''google/rembert''': '''https://huggingface.co/google/rembert/resolve/main/sentencepiece.model''',
    },
}

UpperCamelCase								=		{
    '''google/rembert''': 256,
}

class 				lowerCAmelCase_	(		__snake_case			):
				_UpperCamelCase					:       Tuple							       = VOCAB_FILES_NAMES
				_UpperCamelCase					:       Dict							       = PRETRAINED_VOCAB_FILES_MAP
				_UpperCamelCase					:       List[Any]							       = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES


				def __init__(					self ,						_lowerCAmelCase ,						_lowerCAmelCase=False ,						_lowerCAmelCase=True ,						_lowerCAmelCase=True ,						_lowerCAmelCase="[CLS]" ,						_lowerCAmelCase="[SEP]" ,						_lowerCAmelCase="[UNK]" ,						_lowerCAmelCase="[SEP]" ,						_lowerCAmelCase="[PAD]" ,						_lowerCAmelCase="[CLS]" ,						_lowerCAmelCase="[MASK]" ,						**_lowerCAmelCase ,						):
											super().__init__(
											    do_lower_case=__SCREAMING_SNAKE_CASE ,						remove_space=__SCREAMING_SNAKE_CASE ,						keep_accents=__SCREAMING_SNAKE_CASE ,						bos_token=__SCREAMING_SNAKE_CASE ,						eos_token=__SCREAMING_SNAKE_CASE ,						unk_token=__SCREAMING_SNAKE_CASE ,						sep_token=__SCREAMING_SNAKE_CASE ,						pad_token=__SCREAMING_SNAKE_CASE ,						cls_token=__SCREAMING_SNAKE_CASE ,						mask_token=__SCREAMING_SNAKE_CASE ,						**__SCREAMING_SNAKE_CASE ,						)

											_lowercase							:   str 							=   do_lower_case
											_lowercase							:   Optional[Any] 							=   remove_space
											_lowercase							:   Any 							=   keep_accents
											_lowercase							:   Dict 							=   vocab_file

											_lowercase							:   Tuple 							=   spm.SentencePieceProcessor()
											self.sp_model.Load(__SCREAMING_SNAKE_CASE      )


				@property
				def 						__a					(					self      ):
											return len(self.sp_model      )


				def 						__a					(					self      ):
											_lowercase							:   str 							=   {self.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE      ): i for i in range(self.vocab_size      )}
											vocab.update(self.added_tokens_encoder      )
											return vocab


				def __getstate__(					self      ):
											_lowercase							:   Union[str, Any] 							=   self.__dict__.copy()
											_lowercase							:   str 							=   None
											return state


				def __setstate__(					self ,						_lowerCAmelCase      ):
											_lowercase							:   Optional[Any] 							=   d
											_lowercase							:   List[Any] 							=   spm.SentencePieceProcessor()
											self.sp_model.Load(self.vocab_file      )


				def 						__a					(					self ,						_lowerCAmelCase ,						_lowerCAmelCase=False      ):
											_lowercase							:   Optional[Any] 							=   self.sp_model.EncodeAsPieces(__SCREAMING_SNAKE_CASE      )
											return pieces


				def 						__a					(					self ,						_lowerCAmelCase      ):
											return self.sp_model.PieceToId(__SCREAMING_SNAKE_CASE      )


				def 						__a					(					self ,						_lowerCAmelCase      ):
											return self.sp_model.IdToPiece(__SCREAMING_SNAKE_CASE      )


				def 						__a					(					self ,						_lowerCAmelCase      ):
											_lowercase							:   str 							=   self.sp_model.decode_pieces(__SCREAMING_SNAKE_CASE      )
											return out_string


				def 						__a					(					self ,						_lowerCAmelCase ,						_lowerCAmelCase = None      ):
											_lowercase							:   int 							=   [self.sep_token_id]
											_lowercase							:   Tuple 							=   [self.cls_token_id]
											if token_ids_a is None:
																		return cls + token_ids_a + sep
											return cls + token_ids_a + sep + token_ids_a + sep


				def 						__a					(					self ,						_lowerCAmelCase ,						_lowerCAmelCase = None ,						_lowerCAmelCase = False      ):

											if already_has_special_tokens:
																		if token_ids_a is not None:
																									raise ValueError(
																									    'You should not supply a second sequence if the provided sequence of '
																									    'ids is already formatted with special tokens for the model.'      )
																		return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

											if token_ids_a is not None:
																		return [1] + ([0] * len(__SCREAMING_SNAKE_CASE      )) + [1] + ([0] * len(__SCREAMING_SNAKE_CASE      )) + [1]
											return [1] + ([0] * len(__SCREAMING_SNAKE_CASE      )) + [1]


				def 						__a					(					self ,						_lowerCAmelCase ,						_lowerCAmelCase = None      ):
											_lowercase							:   List[str] 							=   [self.sep_token_id]
											_lowercase							:   List[str] 							=   [self.cls_token_id]

											if token_ids_a is None:
																		return len(cls + token_ids_a + sep      ) * [0]
											return len(cls + token_ids_a + sep      ) * [0] + len(token_ids_a + sep      ) * [1]


				def 						__a					(					self ,						_lowerCAmelCase ,						_lowerCAmelCase = None      ):
											if not os.path.isdir(__SCREAMING_SNAKE_CASE      ):
																		logger.error('Vocabulary path ({}) should be a directory'.format(__SCREAMING_SNAKE_CASE      )      )
																		return
											_lowercase							:   int 							=   os.path.join(
											    __SCREAMING_SNAKE_CASE ,						(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']      )

											if os.path.abspath(self.vocab_file      ) != os.path.abspath(__SCREAMING_SNAKE_CASE      ):
																		copyfile(self.vocab_file ,						__SCREAMING_SNAKE_CASE      )

											return (out_vocab_file,)












"""simple docstring"""





_SCREAMING_SNAKE_CASE   :							Optional[int]          =		8.314_4598







def 	lowerCamelCase__			(				_lowerCamelCase			:						float						,							_lowerCamelCase			:						float					) ->							float:
  if temperature < 0:
    raise Exception('Temperature cannot be less than 0 K'					)
  if molar_mass <= 0:
    raise Exception('Molar mass cannot be less than or equal to 0 kg/mol'					)
  else:
    return (3 * UNIVERSAL_GAS_CONSTANT * temperature / molar_mass) ** 0.5


if __name__ == "__main__":
  import doctest

  # run doctest
  doctest.testmod()

  # example
  _SCREAMING_SNAKE_CASE   :							List[Any]          =		300
  _SCREAMING_SNAKE_CASE   :							Dict          =		28
  _SCREAMING_SNAKE_CASE   :							List[str]          =		rms_speed_of_molecule(temperature, molar_mass)
  print(F'''Vrms of Nitrogen gas at 300 K is {vrms} m/s''')




